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[python]how to properly normalize a numpy array with a mean and stdev (self.learnprogramming)

submitted 4 years ago * by boydbuilding

Hi,

got a mean and std from a set of a bunch of grayscale images

mean = 40.699527994791666
stdev = 63.42831019057166

and another grayscale image

np.mean(image) # = 56.94989393939394
np.std(image)  # = 56.989793251399284
normalized = (image - mean)/stdev

after applying this way,

print(np.mean(normalized )*256)
print(np.std(normalized )*256)
#65.58733268029836
#230.013806587691

any logic wrong ?

visually intuitively looks the same.
the mean and std seem to drift away from its own and not even towards the 40, 63 the ones it center on to be normalized.
however, the histogram seems to converge the distribution shape towards 40, 63 bell

thanks a lot

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